Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Cover of the book

2017 | OriginalPaper | Chapter

1. Introduction to Unconventional Computing

Author : Susan Stepney

Published in: Guide to Unconventional Computing for Music

Publisher: Springer International Publishing

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

This chapter provides a broad overview of the field of unconventional computation, UComp. It includes discussion of novel hardware and embodied systems; software, particularly bio-inspired algorithms; and emergence and open-endedness.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
next chapter On Unconventional Computing for Sound and Music
Footnotes
1
The biological sketches given here are extremely simplified descriptions of highly complex processes.
 
2
Although certain properties of classical systems, such as security and performance, can be considered to be emergent, this emergence is one of the things that makes such properties hard to engineer.
 
Literature
Adamatzky, A. (1994). Constructing a discrete generalized Voronoi diagram in reaction-diffusion media. Neural Networks World, 40(6), 635–644.
Adamatzky, A. (2010). Physarum machines: Computers from slime mould. World Scientific.
Adamatzky, A. (Ed.). (2017a). Advances in unconventional computing, volume 1: Theory. Berlin: Springer.
Adamatzky, A. (Ed.). (2017b). Advances in unconventional computing, volume 2: Prototypes, models and algorithms. Berlin: Springer.
Adamatzky, A., & Martinez, G. J. (Ed.). Designing beauty: The art of cellular automata. Berlin: Springer.
Adamatzky, A., De Lacy Costello, B., & Asai, T. (2005). Reaction-diffusion computers. London: Elsevier.
Adamatzky, A., Kitson, S., De Lacy Costello, B., Matranga, M. A., & Younger. D. (2011). Computing with liquid crystal fingers: Models of geometric and logical computation. Physical Review E: Statistical, Nonlinear, Biological, and Soft Matter Physics, 840(6), 0 061702.
Anderson, P. W. (1972). More is different. Science, 1770(4047), 393–396.
Aristotle. (1924). Metaphysics, book VIII, 350 BCE (trans. by W. D. Ross, Aristotle’s metaphysics), 2 vols. Oxford: Oxford University Press.
Armstrong, R. (2015). How do the origins of life sciences influence 21st century design thinking? In ECAL 2015 (pp. 2–11). Cambridge: MIT Press.
Armstrong, R. (2017). Experimental architecture and unconventional computing (pp. 773–804). In Adamatzky2017v2.
Banzhaf, W., & Yamamoto, L. (2015). Artificial chemistries. Cambridge. MIT Press.
Banzhaf, W., Baumgaertner, B., Beslon, G., Doursat, R., Foster, J. A., McMullin, B., … & White, R. (2016). Defining and simulating open-ended novelty: Requirements, guidelines, and challenges. Theory in Biosciences, 135(3), 131–161.
Beal, J., Viroli, M. (2015). Space-time programming. Philosophical Transactions of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, 3730(2046).
Braund, E., & Miranda, E. (2015). Music with unconventional computing: Towards a step sequencer from plasmodium of Physarum polycephalum. In EvoMusArt 2015, volume 9027 of LNCS (pp. 15–26). Berlin: Springer.
Broersma, H., Miller, J. F., & Nichele, S. (2017). Computational matter: Evolving computational functions in nanoscale materials (pp. 397–428). In Adamatzky2017v2.
Brooks, R. A. (1991). How to build complete creatures rather than isolated cognitive simulators (pp. 225–239). In Architectures for intelligence: 22nd Carnegie Mellon Symposium on Cognition.
Callan, R. (1999). The essence of neural networks. New York: Prentice Hall.
Campbell, D., Farmer, D., Crutchfield, J., & Jen, E. (1985). Experimental mathematics: The role of computation in nonlinear science. Communications of ACM, 280(4), 374–384.
Cockshott, P., Mackenzie, L. M., & Michaelson, G. (2012). Computation and its limits. New York: Oxford University Press.
Collins, S., Ruina, A., Tedrake, R., & Wisse, M. (2005). Efficient bipedal robots based on passive-dynamic walkers. Science, 3070(5712), 1082–1085.
Copeland, B. J. (2004). Hypercomputation: Philosophical issues. Theoretical Computer Science, 3170(1–3), 251–267.
Dale, M., Miller, J. F., Stepney, S., & Trefzer, M. A. (2016). Evolving carbon nanotube reservoir computers. In UCNC 2016, volume 9726 of LNCS (pp. 49–61). Berlin: Springer.
Dale, M., Miller, J. F., & Stepney, S. (2017). Reservoir computing as a model for in materio computing (pp. 533–571). In Adamatzky2017v1.
de Castro, L. N., & Timmis, J. (2002). Artificial immune systems: A new computational intelligence approach. Berlin: Springer.
Deutsch, D. (1997). The fabric of reality. Penguin.
Dittrich, P., Ziegler, J., & Banzhaf, W. (2001). Artificial chemistries—A review. Artificial Life, 70(3), 225–275.
Dorigo, M., Maniezzo, V., & Colorni, A. (1996). Ant system: Optimization by a colony of cooperating agents. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 260(1), 29–41.
Doursat, R., Sayama, H., & Michel, O. (Eds.), Morphogenetic engineering: Towards programmable complex systems. Berlin: Springer.
Feynman, R. P. (1982). Simulating physics with computers. International Journal of Theoretical Physics, 210(6–7), 467–488.
Gardner, M. (1970). The fantastic combinations of John Conway’s new solitaire game “life’’. Scientific American, 120–123, October 1970.
Gatys, L. A., Ecker, A. S., & Bethge, M. (2015). A neural algorithm of artistic style. CoRR, abs/1508.06576, arxiv.org/abs/1508.06576.
Grover, L. K. (1996). A fast quantum mechanical algorithm for database search. In Proceedings of the Twenty-Eighth Annual ACM Symposium on Theory of Computing (pp. 212–219), ACM.
Harding, S., & Miller, J. F. (2004). Evolution in materio: A tone discriminator in liquid crystal. In Congress on Evolutionary Computation (CEC2004) (Vol. 2, pp. 1800–1807).
Hickinbotham, S., & Stepney, S. (2016). Augmenting live coding with evolved patterns. In EvoMusArt 2016, (vol. 9596, pp. 31–46). Berlin: Springer, LNCS.
Hornby, G. S. (2004). Functional scalability through generative representations: The evolution of table designs. Environment and Planning. B: Planning and Design, 310(4), 569–587.
Horsman, C., Stepney, S., & Kendon, V. (2014a). When does an unconventional substrate compute? UCNC 2014 Poster Proceedings, University of Western Ontario Technical Report 758.
Horsman, C., Stepney, S., Wagner, R. C., & Kendon. V. (2014b). When does a physical system compute? Proceedings of the Royal Society A, 4700(2169), 182.
Horsman, D., Kendon, V., Stepney, S., & Young, P. (2017). Abstraction and representation in living organisms: When does a biological system compute? In G. Dodig-Crnkovic, & R. Giovagnoli (Eds.), Representation and reality: Humans, animals, and machines. Berlin: Springer (in press).
Jaeger, H. (2001). The “echo state” approach to analysing and training recurrent neural networks. GMD Technical Report 148, German National Research Center for Information Technology, Bonn, Germany, 2001 (with an Erratum note, 2010).
Johnson, M. W., et al. (2011). Quantum annealing with manufactured spins. Nature, 4730(7346), 194–198.
Kadowaki, T., & Nishimori, H. (1998). Quantum annealing in the transverse Ising model. Physical Review E, 580(5), 5355–5363.
Kennedy, J., & Eberhart, R. (1995). Particle swarm optimization. In IEEE International Conference on Neural Networks 1995 (vol. 4, pp. 1942–1948).
Kirkpatrick, S., Gelatt, C. D. Jr, & Vecchi, M. P. (1983). Optimization by simulated annealing. Science, 2200(4598), 671–680.
Lanting, T., et al. (2014). Entanglement in a quantum annealing processor. Physical Review X, 40(2), 021041.
Lehman, J., & Stanley, K. O. (2011). Abandoning objectives: Evolution through the search for novelty alone. Evolutionary Computation 1, 190(2), 189–223.
Lones, M. A., Turner, A. P., Fuente, L. A., Stepney, S., Caves, L. S. D., & Tyrrell, M. (2013). Biochemical connectionism. Natural Computing, 120(4), 453–472.
Maass, W., Natschläger, T., & Markram, H. (2002). Real-time computing without stable states: A new framework for neural computation based on perturbations. Neural Computation, 140(11), 2531–2560.
Mandelbrot, B. B. (1997). The fractal geometry of nature. Freeman.
Miller, J. F., & Downing, K. (2002). Evolution in materio: Looking beyond the silicon box. In Proceedings of NASA/DoD Conference on Evolvable Hardware, 2002 (pp. 167–176).
Miller, J. F., Harding, S. L., & Tufte, G. (2014). Evolution-in-materio: Evolving computation in materials. Evolutionary Intelligence, 70(1), 49–67.
Mills, J. W., Parker, M., Himebaugh, B., Shue, C., Kopecky, B., & Weilemann, C. (2006). “Empty space” computes: The evolution of an unconventional supercomputer. In Proceedings of the 3rd Conference on Computing Frontiers, CF ’06 (pp. 115–126).
Miranda, E. R., & Braund, E. (2017). Experiments in musical biocomputing: Towards new kinds of processors for audio and music (pp. 739–761). In Adamatzky2017v2.
Mitchell, M. (1996). An introduction to genetic algorithms. Cambridge: MIT Press.
Mohid, M., Miller, J. F., Harding, S. L., Tufte, G., Massey, M. K.,et al. (2015). Evolution-in-materio: Solving computational problems using carbon nanotube–polymer composites. Soft Computing 1–16.
Newborough, J., & Stepney, S. (2005). A generic framework for population-based algorithms, implemented on multiple FPGAs. In ICARIS 2005, volume 3627 of LNCS (pp. 43–55). Berlin: Springer.
Nielsen, M. A., & Chuang, I. L. (2000). Quantum computation and quantum information. Cambridge: Cambridge University Press.
Owens, N., & Stepney, S. (2010). The game of life rules on Penrose tilings. In A. Adamatzky (Ed.), Game of life cellular automata (pp. 331–378). Springer, Berlin.
Pease, R. (2013). How to turn living cells into computers. Nature News, February 2013.
Prusinkiewicz, P., & Lindenmayer, A. (1990). The algorithmic beauty of plants. Berlin: Springer.
Rendell, P. (2002). Turing universality of the Game of Life. In Andrew Adamatzky, editor, Collision-Based Computing, pages 513–539. Berlin: Springer.
Rubel, L. A. (1993). The extended analog computer. Advances in Applied Mathematics, 140(1), 39–50.
Santoro, G. E., & Tosatti, E. (2006). Optimization using quantum mechanics: Quantum annealing through adiabatic evolution. Journal of Physics A, 390(36), R393.
Shannon, C. E. (1941). Mathematical theory of the differential analyzer. Journal of Mathematics and Physics, 200(1–4), 337–354.
Shor, P. W. (1997). Polynomial-time algorithms for prime factorization and discrete logarithms on a quantum computer. SIAM Journal on Computing, 260(5), 1484–1509.
Stanley, K. O. (2007). Compositional pattern producing networks: A novel abstraction of development. Genetic Programming and Evolvable Machines, 80(2), 131–162.
Stanley, K. O., & Miikkulainen, R. (2002). Evolving neural networks through augmenting topologies. Evolutionary Computation, 100(2), 99–127.
Stanley, K. O., D’Ambrosio, D. B., & Gauci, J. (2009). A hypercube-based encoding for evolving large-scale neural networks. Artificial Life, 150(2), 185–212.
Steil, J. J. (2004). Backpropagation-decorrelation: Online recurrent learning with o(n) complexity. In 2004 IEEE International Joint Conference on Neural Networks (vol. 2, pp. 843–848). IEEE.
Steinbock, O., Tóth, A., & Showalter, K. (1995). Navigating complex labyrinths: Optimal paths from chemical waves. Science, 2670(5199), 868–871.
Stepney, S. (2007). Embodiment. In D. Flower, & J. Timmis (Eds.), In silico immunology, pp.265–288. Berlin: Springer.
Stepney, S. (2008). The neglected pillar of material computation. Physica D, 2370(9), 1157–1164.
Stepney, S. (2012a). Non-classical computation: A dynamical systems perspective. In G. Rozenberg, T. Bäck, & Kok, J. N. (Eds.), Handbook of natural computing (pp. 1979–2025). Berlin: Springer.
Stepney, S. (2012b). Programming unconventional computers: Dynamics, development, self-reference. Entropy, 140(12), 1939–1952.
Stepney, S., Abramsky, S., Adamatzky, A., Johnson, C. G., & Timmis, J. (2008). Grand challenge 7: Journeys in non-classical computation. In Visions of Computer Science, London, UK (pp. 407–421), BCS.
Stepney S, Diaconescu A, Doursat, R., Giavitto, J. -L., Kowaliw, T., Leyser, O., et al. (2012). Gardening cyber-physical systems. In UCNC 2012, vol. 7445 of LNCS (pp. 237–238). Berlin: Springer.
Stovold, J., & O’Keefe, S. (2017). Associative memory in reaction-diffusion chemistry (pp. 141–166). In Adamatzky2017v2.
Swade, D. (1995). Charles Babbage’s difference engine no. 2: Technical description. Science Museum Papers in the History of Technology 4, September 1995.
Todd, S., & Latham, W. (1992). Evolutionary art and computers. New York: Academic Press.
Turing. A.M. (1952). The chemical basis of morphogenesis. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 2370(641), 37–72.
Wegner, P. (1997). Why interaction is more powerful than algorithms. Commun. ACM, 400(5), 80–91.
Winfree, E. (2004). DNA computing by self-assembly. In 2003 NAE Symposium on Frontiers of Engineering (pp. 105–117). Washington, DC: National Academies Press.
Worth, P., & Stepney, S. (2005). Growing music: Musical interpretations of L-systems. In EvoMusArt 2005, vol. 3449 of LNCS (pp. 545–550). Berlin: Springer.
Metadata
Title
Introduction to Unconventional Computing
Author
Susan Stepney
Copyright Year
2017
Book
Guide to Unconventional Computing for Music

Print ISBN: 978-3-319-49880-5

Electronic ISBN: 978-3-319-49881-2

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-49881-2_1

Premium Partner

    Image Credits